Patient-reported outcomes after minimally invasive sacro-iliac joint surgery: a cohort study based on the Swedish Spine Registry

Background and purpose There is conflicting evidence regarding treatment outcomes after minimally invasive sacroiliac joint fusion for long-lasting severe sacroiliac joint pain. The primary aim of our cohort study was to investigate change in patient-reported outcome measures (PROMs) after minimally invasive sacroiliac joint surgery in daily practice in the Swedish Spine Registry. Secondary aims were to explore the proportion of patients reaching a patient acceptable symptom score (PASS) and the minimal clinically important difference (MCID) for pain scores, physical function, and health-related quality of life outcomes; furthermore, to evaluate self-reported satisfaction, walking distance, and changes in proportions of patients on full sick leave/disability leave and report complications and reoperations. Methods Data from the Swedish Spine Registry was collected for patients with first-time sacroiliac joint fusion, aged 21 to 70 years, with PROMs available preoperatively, at 1 or 2 years after last surgery. PROMs included Oswestry Disability Index (ODI), Numeric Rating Scale (NRS) for low back pain (LBP) and leg pain, and EQ-VAS, in addition to demographic variables. We calculated mean change from pre- to postoperative and the proportion of patients achieving MCID and PASS. Results 68 patients had available pre- and postoperative data, with a mean age of 45 years (range 25–70) and 59 (87%) were female. At follow-up the mean reduction was 2.3 NRS points (95% confidence interval [CI] 1.6–2.9; P < 0.001) for LBP and 14.8 points (CI 10.6–18.9; P < 0.001) for ODI. EQ-VAS improved by 22 points (CI 15.4–30.3, P < 0.001) at follow-up. Approximately half of the patients achieved MCID and PASS for pain (MCID NRS LBP: 38/65 [59%] and PASS NRS LBP: 32/66 [49%]) and physical function (MCID ODI: 27/67 [40%] and PASS ODI: 24/67 [36%]). The odds for increasing the patient’s walking distance to over 1 km at follow-up were 3.5 (CI 1.8–7.0; P < 0.0001), and of getting off full sick leave or full disability leave was 0.57 (CI 0.4–0.8; P = 0.001). In the first 3 months after surgery 3 complications were reported, and in the follow-up period 2 reoperations. Conclusion We found moderate treatment outcomes after minimally invasive sacroiliac joint fusion when applied in daily practice with moderate pain relief and small improvements in physical function.


Structure of and data collec0on in Swespine
Data is collected into Swespine through an opt-out method where ques7onnaires with PROMs (NRS, ODI, EQ-VAS and more) and demographic ques7ons (age, sex, work status, walking distance, sa7sfac7on, medica7on, etc.) are sent the pa7ents by post [1].Both filling out the ques7onnaires and returning them is voluntary [1].All preopera7ve baseline data and postopera7ve follow-up data is mainly pa7ent based [1].Therefore, the availability of the data in Swespine is dependent on the pa7ent´s willingness to fill out and return ques7onnaires.The surgical data (related to the opera7on) are the only data completed by the surgeon at the 7me of discharge from the hospital including diagnosis, procedure, implant, hospitaliza7on 7me, an7bio7c prophylaxis and occurrence of complica7ons [1].Any reopera7ons or complica7ons must be reported by the surgeon and are dependent on the compliance and willingness of the surgeon to supply data into Swespine [1].

Missing data in Swespine
When a sample of pa7ents with a certain procedure are extracted from Swespine for analysis, there will be various amounts of missing data due to the manner Swespine is organized and data is collected.The data will be missing at random and cannot be ignored when doing sta7s7cal analysis.

Handling of missing data in the current cohort study
Missing data can be "missing completely at random", which are the only kind of missing data that can be ignored, or data can be "missing at random" [2,3].When data is "missing at random" certain sta7s7cal techniques can be used to handle such missing data.In the current cohort study, we chose to use a mul7ple imputa7on model to evaluate the influence of missing data on the results (Tables 1b, 2c, 3c, 4c and 5c).Results obtained from the mul7ple imputa7on model were compared to the results found by using a "Last Observa7on Carried Forward" (LOCF) method.The LOCF data contained 68 pa7ents, where 1 year data was carried forward to 2 years in the cases where 2-year data were missing (Tables 1a, 2b, 3b, 4b and 5b).In addi7on, a complete case analysis was done (where all missing data were deleted analysis by analysis) to evaluate the difference in results between the three methods.Results obtained from the complete case analysis are presented in Tables 2a, 3a, 4a and 5a.

Mul0ple imputa0on model for missing data
A mul7ple imputa7on model was used to complete missing data for the iden7fied 116 pa7ents who had undergone sacroiliac joint fusion and who fulfilled the inclusion criteria for the current study [2,3].A mul7ple imputa7on with 20 imputa7ons was done using SPSS [2].
Complete variables at baseline were used as predictors for imputa7on and consisted of age, sex and opera7ng center.In addi7on, all variables with missing data were used to run the imputa7on model.The mul7ple imputa7on model was executed using default sedngs and adding appropriate clinical and/or scale limits to each missing variable.The imputed data sets were used for analysis to obtain pooled analysis results.The analyses resul7ng from pooled imputed data are presented in Tables 1b, 2c, 3c, 4c and 5c.

Tables 1 to 5 presen?ng baseline characteris?cs and outcome data based on Last
Observa?on Carried Forward and Imputed data   For Abbrevia)ons, see Table 2a.For Abbrevia)ons, see Table 2a and N/A = Not available.

3. 4
Tables showing walking distance before and aGer sacroiliac joint fusion 3.4.1

Table 1b .
Pa'ent baseline characteris'cs.Analyses were done using a mul'ple imputa'on model and presents data of all 116 pa'ents.Values are count/total number (%) unless otherwise specified

Tables presen0ng outcomes of pain, physical func0on and health related quality of life 3
.2.1 Table 2a.Outcome on pain, physical func'on and health related quality of life.Complete case data with deleted missing data analysis by analysis

Table 2b .
Outcome on pain, physical func'on and health related quality of life.Data shown as mean with (SD) or (CI).Analysis based on last observa'on carried forward (1 year data are carried forward to 2 year)

Table 2c .
Outcome in regard of pain, physical func'on and health related quality of life.Data

3 Tables showing propor0on of pa0ents reaching pa0ents acceptable symptom state, 30% improvement in outcome and minimal clinical important difference 3
.3.1 Table 3a.Propor'on of pa'ents reaching pa'ents acceptable symptom state, 30% improvement in outcome, and minimal clinical important difference.Complete case data with missing data deleted analysis by analysis For Abbrevia)ons, see Table 2a and N/A = Not available.

Table 3b .
Propor'on of pa'ents reaching pa'ents acceptable symptom state, 30% increase in outcome and minimal clinical important difference.Analysis based on LOCF method, N = 68

Table 3c .
Propor'on of pa'ents reaching pa'ents acceptable symptom state, 30% improvement in outcome, and minimal clinical important difference.Analysis on imputed data from mul'ple imputa'on model For Abbrevia)ons, see Table2aand N/A = Not available.

Table 4a .
Walking distance before and aier sacroiliac joint fusion.Complete case analysis with missing data deleted analysis by analysis Table4b.Walking distance before and aier sacroiliac joint fusion.Analysis from LOCF

Table 4c .
Walking distance before and aier sacroiliac joint fusion.Analysis on imputed data